Search results for: multiple optimal solutions

Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

Abstract:

As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Ons Triki, Fathi Abid

Abstract:

Along with the increase in the use of leasing contracts in corporate finance, multiple studies aim to model the credit risk of the lease in order to cover the losses of the lessor of the asset if the lessee goes bankrupt. In the current research paper, a convertible lease contract is elaborated in a continuous time stochastic universe aiming to ensure the financial stability of the firm and quickly recover the losses of the counterparties to the lease in case of default. This work examines the term structure of the lease rates taking into account the credit default risk and the capital structure of the firm. The interaction between the lessee's capital structure and the equilibrium lease rate has been assessed by applying the competitive lease market argument developed by Grenadier (1996) and the endogenous structural default model set forward by Leland and Toft (1996). The cumulative probability of default was calculated by referring to Leland and Toft (1996) and Yildirim and Huan (2006). Additionally, the link between lessee credit risk and lease rate was addressed so as to explore the impact of convertible lease financing on the term structure of the lease rate, the optimal leverage ratio, the cumulative default probability, and the optimal firm value by applying an endogenous conversion threshold. The numerical analysis is suggestive that the duration structure of lease rates increases with the increase in the degree of the market price of risk. The maximal value of the firm decreases with the effect of the optimal leverage ratio. The results are indicative that the cumulative probability of default increases with the maturity of the lease contract if the volatility of the asset service flows is significant. Introducing the convertible lease contract will increase the optimal value of the firm as a function of asset volatility for a high initial service flow level and a conversion ratio close to 1.

Keywords: convertible lease contract, lease rate, credit-risk, capital structure, default probability

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Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

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Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim

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As the penetration of Energy Storage System (ESS) increases in the power system due to higher performance and lower cost than ever, ESS is expanding its role to the ancillary service as well as the storage of extra energy from the intermittent renewable energy resources. For multi-ESS with different capacity and SOC level each other, it is required to make the optimal schedule of SOC level use the multi-ESS effectively. This paper proposes the energy allocation method for the multiple battery ESS with reliability constraint, in order to make the ESS discharge the required energy as long as possible. A simple but effective method is proposed in this paper, to satisfy the power for the spinning reserve requirement while improving the system reliability. Modelling of ESS is also proposed, and reliability is evaluated by using the combined reliability model which includes the proposed ESS model and conventional generation one. In the case study, it can be observed that the required power is distributed to each ESS adequately and accordingly, the SOC is scheduled to improve the reliability indices such as Loss of Load Probability (LOLP) and Loss of Load Expectation (LOLE).

Keywords: multiple energy storage system (MESS), energy allocation method, SOC schedule, reliability constraints

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Authors: Marlene Perez Villalpando, Kelly Joel Gurubel Tun

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In this paper, we propose an optimal control strategy for a hydroelectric power plant subject to input disturbances like meteorological phenomena. The engineering characteristics of the system are described by a nonlinear model. The random availability of renewable sources is predicted by a high-order neural network trained with an extended Kalman filter, whereas the power generation is regulated by the optimal control law. The main advantage of the system is the stabilization of the amount of power generated in the plant. A control supervisor maintains stability and availability in hydropower reservoirs water levels for power generation. The proposed approach demonstrated a good performance to stabilize the reservoir level and the power generation along their desired trajectories in the presence of disturbances.

Keywords: hydropower, high order neural network, Kalman filter, optimal control

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Authors: N. Pitcheswara Rao

Abstract:

In the process of conveying the information there may be a chance of signal being corrupted which leads to the erroneous bits in the message. The message may consist of single, double and multiple bit errors. In high-reliability applications, memory can sustain multiple soft errors due to single or multiple event upsets caused by environmental factors. The traditional hamming code with SEC-DED capability cannot be address these types of errors. It is possible to use powerful non-binary BCH code such as Reed-Solomon code to address multiple errors. However, it could take at least a couple dozen cycles of latency to complete first correction and run at a relatively slow speed. In order to overcome this drawback i.e., to increase speed and latency we are using reed-Muller code.

Keywords: SEC-DED, BCH code, Reed-Solomon code, Reed-Muller code

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Authors: Xu Runzhang, Yang Yanbing, Niu Yi, Zhang Mingyou, Liu Yu

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For a class of semilinear parabolic equations with linear dynamical boundary conditions in a bounded domain, we obtain both global solutions and finite time blow-up solutions when the initial data varies in the phase space H1(Ω). Our main tools are the comparison principle, the potential well method and the concavity method. In particular, we discuss the behavior of the solutions with the initial data at critical and high energy level.

Keywords: high energy level, critical energy level, linear dynamical boundary condition, semilinear parabolic equation

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Authors: Dharminder Singh, Sanjeev Yadav, Pravakar Mohanty

Abstract:

In this work, study of temperature profile in a pilot scale air bubbling fluidized bed (ABFB) gasifier for rice husk gasification was carried out. Effects of different factors such as multiple cyclones, gas cooling system, ventilate gas pipe length, and catalyst on temperature profile was examined. ABFB gasifier used in this study had two sections, one is bed section and the other is freeboard section. River sand was used as bed material with air as gasification agent, and conventional charcoal as start-up heating medium in this gasifier. Temperature of different point in both sections of ABFB gasifier was recorded at different ER value and ER value was changed by changing the feed rate of biomass (rice husk) and by keeping the air flow rate constant for long durational of gasifier operation. ABFB with double cyclone with gas coolant system and with short length ventilate gas pipe was found out to be optimal gasifier design to give temperature profile required for high gasification performance in long duration operation. This optimal design was tested with different ER values and it was found that ER of 0.33 was most favourable for long duration operation (8 hr continuous operation), giving highest carbon conversion efficiency. At optimal ER of 0.33, bed temperature was found to be stable at 700 °C, above bed temperature was found to be at 628.63 °C, bottom of freeboard temperature was found to be at 600 °C, top of freeboard temperature was found to be at 517.5 °C, gas temperature was found to be at 195 °C, and flame temperature was found to be 676 °C. Temperature at all the points showed fluctuations of 10 – 20 °C. Effect of catalyst i.e. dolomite (20% with sand bed) was also examined on temperature profile, and it was found that at optimal ER of 0.33, the bed temperature got increased to 795 °C, above bed temperature got decreased to 523 °C, bottom of freeboard temperature got decreased to 548 °C, top of freeboard got decreased to 475 °C, gas temperature got decreased to 220 °C, and flame temperature got increased to 703 °C. Increase in bed temperature leads to higher flame temperature due to presence of more hydrocarbons generated from more tar cracking at higher temperature. It was also found that the use of dolomite with sand bed eliminated the agglomeration in the reactor at such high bed temperature (795 °C).

Keywords: air bubbling fluidized bed gasifier, bed temperature, charcoal heating, dolomite, flame temperature, rice husk

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Authors: Pitcheswara Rao Nelapati

Abstract:

In the process of conveying the information there may be a chance of signal being corrupted which leads to the erroneous bits in the message. The message may consist of single, double and multiple bit errors. In high-reliability applications, memory can sustain multiple soft errors due to single or multiple event upsets caused by environmental factors. The traditional hamming code with SEC-DED capability cannot be address these types of errors. It is possible to use powerful non-binary BCH code such as Reed-Solomon code to address multiple errors. However, it could take at least a couple dozen cycles of latency to complete first correction and run at a relatively slow speed. In order to overcome this drawback i.e., to increase speed and latency we are using reed-Muller code.

Keywords: SEC-DED, BCH code, Reed-Solomon code, Reed-Muller code

Procedia PDF Downloads 422

Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

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With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

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Authors: Geraldine O’Neill

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Work-integrated learning is a valuable learning experience for students in higher education. However, the fairness of the assessment process has been identified as a challenge. This study explored solutions to this challenge through interviews with expert authors in the field and workshops across nine different disciplines in Ireland. In keeping with the use of a participatory and action research methodology, the key stakeholders in the process, the students, educators, and practitioners, identified some solutions. The solutions included the need to: clarify the assessments’ expectations; enhance the flexibility of the competencies, reduce the number of competencies; use grading scales with lower specificity; support practitioner training, and empower students in the assessment process. The results are discussed as they relate to interactional, procedural, and distributive fairness.

Keywords: competencies, fairness, grading scales, work-integrated learning

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Authors: Jaehong Yu, Seoung Bum Kim

Abstract:

Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

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We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take dierent specic cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

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Authors: P. Parthiban, Sonu Rajak, N. Kannan, R. Dhanalakshmi

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This paper deals with the Vehicle Routing Problem (VRP) with environmental considerations which is called Pollution Routing Problem (PRP). The objective is to minimize the operational and environmental costs. It consists of routing a number of vehicles to serve a set of customers, and determining fuel consumption, driver wages and their speed on each route segment, while respecting the capacity constraints and time windows. In this context, we presented an Ant Colony Optimization (ACO) approach, combined with a Speed Optimization Algorithm (SOA) to solve the PRP. The proposed solution method consists of two stages. Stage one is to solve a Vehicle Routing Problem with Time Window (VRPTW) using ACO and in the second stage a SOA is run on the resulting VRPTW solutions. Given a vehicle route, the SOA consists of finding the optimal speed on each arc of the route in order to minimize an objective function comprising fuel consumption costs and driver wages. The proposed algorithm tested on benchmark problem, the preliminary results show that the proposed algorithm is able to provide good solutions.

Keywords: ant colony optimization, CO2 emissions, combinatorial optimization, speed optimization, vehicle routing

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Authors: Mario Calabrese, Francesca Iandolo, Pietro Vito, Raffaele D'Amore, Francesco Caputo

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This article presents a synopsis of Nature-Based Solutions (NBS), a fresh and emerging concept in mitigating and adapting to climate change. It outlines a classification of NBS, from the least intrusive to the most advanced engineering, and provides illustrations of each. Moreover, it gives an overview of the 'Life Metro Adapt' initiative, which dealt with the climatic challenges faced by the Milan Metropolitan City and encouraged the development of climate change adaptation methods using alternative, nature-focused solutions. Lastly, the article emphasizes the necessity of raising awareness about environmental issues to ensure that NBS becomes a regular practice today and can be refined in the future.

Keywords: nature-based solutions, urban resilience, climate change adaptation, life metro adapt initiative

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

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In order to sustain the advantages of an advanced manufacturing technique, such as laser sintering, minimization of total processing cost of the parts being produced is very important. An efficient time management would usually very important in optimal cost attainment which would ultimately result in an efficient advanced manufacturing process planning and control. During Laser Scanning Process Scanning (SLS) procedures it is possible to adjust various manufacturing parameters which are used to influence the improvement of various mechanical and other properties of the products. In this study, Modelling and mathematical analysis, including sensitivity analysis, of the laser sintering process time were carried out. The results of the analyses were represented with graphs, from where conclusions were drawn. It was specifically observed that achievement of optimal total scanning time is key for economic efficiency which is required for sustainability of the process.

Keywords: modeling and analysis, optimal planning and control, laser sintering process, scanning time

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Authors: Sujan Tyata, Alison Shilpakar, Nayan Bakhadyo, Kushal K. C., Abhas Maskey

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The Koshi River, acknowledged as the "Sorrow of Bihar," poses intricate challenges characterized by recurrent flooding. Within the Koshi Basin, floods have historically inflicted damage on infrastructure, agriculture, and settlements. The Koshi River exhibits a highly braided pattern across a 48 km stretch to the south of Chatara. The devastating flood from the Koshi River, which began in Nepal's Sunsari District in 2008, led to significant casualties and the destruction of agricultural areas.The catastrophe was exacerbated by a levee breach, underscoring the vulnerability of the region's flood defenses. A comprehensive understanding of environmental changes in the area is unveiled through satellite imagery analysis. This analysis facilitates the identification of high-risk zones and their contributing factors. Employing remote sensing, the analysis specifically pinpoints locations vulnerable to levee breaches. Topographical features of the area along with longitudinal and cross sectional profiles of the river and levee obtained from digital elevation model are used in the hydrological analysis for assessment of flood. To mitigate the impact of floods, the strategy involves the establishment of reservoirs upstream. Leveraging satellite data, optimal locations for water storage are identified. This approach presents a dual opportunity to not only alleviate flood risks but also catalyze the implementation of pumped storage hydropower initiatives. This holistic approach addresses environmental challenges while championing sustainable energy solutions.

Keywords: flood mitigation, levee, remote sensing, satellite imagery analysis, sustainable energy solutions

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Authors: Abderrahim Siam, Ramdane Maamri, Zaidi Sahnoun

Abstract:

The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines. The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques, and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets

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Authors: Angely Sim Jia Wun, Sasa Arsovski

Abstract:

Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Sh. Gofurov, O. Ismailova, U. Makhmanov, A. Kokhkharov

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The refractometric method has been used to determine optical properties of concentration features of aqueous solutions of ethanol, tetrahydrofuran and dimethylformamide at the room temperature. Changes in dielectric permittivity of aqueous solutions of ethanol, tetrahydrofuran and dimethylformamide in a wide range of concentrations (0÷1.0 molar fraction) have been studied using molecular dynamics method. The curves depending on the concentration of experimental data on excess refractive indices and excess dielectric permittivity were compared. It has been shown that stable heteromolecular complexes in binary solutions are formed in the concentration range of 0.3÷0.4 mole fractions. The real and complex part of dielectric permittivity was obtained from dipole-dipole autocorrelation functions of molecules. At the concentrations of C = 0.3 / 0.4 m.f. the heteromolecular structures with hydrogen bonds are formed. This is confirmed by the extremum values of excessive dielectric permittivity and excessive refractive index of aqueous solutions.

Keywords: refractometric method, aqueous solution, molecular dynamics, dielectric constant

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Authors: Mohammad Javad Maghsoudi, Z. Mohamed, A. R. Husain

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Input shaping has been utilized for vibration reduction of many oscillatory systems. This paper presents an optimal closed-loop input shaping scheme for control of a three dimensional (3D) gantry crane system including. This includes a PID controller and Zero Vibration shaper which consider two control objectives concurrently. The control objectives are minimum sway of a payload and fast and accurate positioning of a trolley. A complete mathematical model of a lab-scaled 3D gantry crane is simulated in Simulink. Moreover, by utilizing PSO algorithm and a proposed scheme the controller is designed to cater both control objectives concurrently. Simulation studies on a 3D gantry crane show that the proposed optimal controller has an acceptable performance. The controller provides good position response with satisfactory payload sway in both rail and trolley responses.

Keywords: 3D gantry crane, input shaping, closed-loop control, optimal scheme, PID

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Authors: Palwinder Singh, Munish Sandhir, Tejinder Singh

Abstract:

The ordinary differential equations (ODE) represent a natural framework for mathematical modeling of many real-life situations in the field of engineering, control systems, physics, chemistry and astronomy etc. Such type of differential equations can be solved by analytical methods or by numerical methods. If the solution is calculated using analytical methods, it is done through calculus theories, and thus requires a longer time to solve. In this paper, we compare the numerical accuracy of the solutions given by the three main types of one-step initial value solvers: Taylor’s Series Method, Euler’s Method and Runge-Kutta Fourth Order Method (RK4). The comparison of accuracy is obtained through comparing the solutions of ordinary differential equation given by these three methods. Furthermore, to verify the accuracy; we compare these numerical solutions with the exact solutions.

Keywords: Ordinary differential equations (ODE), Taylor’s Series Method, Euler’s Method, Runge-Kutta Fourth Order Method

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Authors: Dao Phuong Nam, Tran Van Tuyen, Do Trong Tan, Bui Minh Dinh, Nguyen Van Huong

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In this paper, we investigate the adaptive optimal control law for continuous-time systems with input disturbances and unknown parameters. This paper extends previous works to obtain the robust control law of uncertain systems. Through theoretical analysis, an adaptive dynamic programming (ADP) based optimal control is proposed to stabilize the closed-loop system and ensure the convergence properties of proposed iterative algorithm. Moreover, the global asymptotic stability (GAS) for closed system is also analyzed. The theoretical analysis for continuous-time systems and simulation results demonstrate the performance of the proposed algorithm for an inverted pendulum system.

Keywords: approximate/adaptive dynamic programming, ADP, adaptive optimal control law, input state stability, ISS, inverted pendulum

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Authors: Zoran Visak, Joana Lopes, Vesna Najdanovic-Visak

Abstract:

Within this study, the separation of nicotine from its aqueous solutions, using inorganic salt sodium chloride or ionic liquid (molten salt) ECOENG212® as salting-out media, was carried out. Thus, liquid-liquid equilibria of the ternary solutions (nicotine+water+NaCl) and (nicotine+water+ECOENG212®) were determined at ambient pressure, 0.1 MPa, at three temperatures. The related phase diagrams were constructed in two manners: by adding the determined cloud-points and by the chemical analysis of phases in equilibrium (tie-line data). The latter were used to calculate two important separation parameters - partition coefficients of nicotine and separation factors. The impacts of the initial compositions of the mother solutions and of temperature on the liquid-liquid phase separation and partition coefficients were analyzed and discussed. The results obtained clearly showed that both investigated salts are good salting-out media for the efficient and sustainable separation of nicotine from its solutions with water. However, when compared, sodium chloride exhibited much better separation performance than the ionic liquid.

Keywords: nicotine, liquid-liquid separation, inorganic salt, ionic liquid

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Authors: Hossein Shokouhmand, Seyyed Mostafa Saadat

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In this paper, the effect of thermal dispersion on the performance of plate heat exchangers (PHEs) with sinusoidal plates is investigated. In this regard, the PHE is considered as a porous medium. The important property of a porous medium is porosity that is defined as the total fluid volume divided by the total volume occupied by the solid and fluid. A 2D array of parallel sinusoidal plates with laminar periodically developed forced convection and single-phase constant property flows and conduction in a homogenous solid phase in two directions is considered. The array of flows is counter and the flows heat capacities are equal. Numerical study of conjugate heat transfer and axial conduction in the solid phase with different plate thicknesses showed that there is an optimal porosity in which the efficiency of heat transfer is up to 4% more than the time when the porosity is near one. It is shown that the optimal porosity at zero angle of inclination depends both on Reynolds number and the aspect ratio. The optimal porosity increased while either the Reynolds number or waviness of plates increased.

Keywords: plate heat exchanger, optimal porosity, efficiency, aspect ratio

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Authors: Jay Xiong, Li Lin

Abstract:

Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

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Authors: Gopinath Rathod, Vinod Puranik

Abstract:

Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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Authors: Yuyang Cheng, Marcos Escobar-Anel

Abstract:

This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market.

Keywords: stochastic covariance process, 4/2 stochastic volatility model, stochastic co-volatility movements, characteristic function, expected utility theory, verication theorem

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Authors: S. Pooja Pragati, B. Sudarsan, S. Raj Kumar

Abstract:

This paper provides a practical design of a new concept of massive Induced Drag reductions of stream vise staggered multiple winglets. It is designed to provide an optimum performance of a winglet from conventional designs. In preparing for a mechanical design, aspects such as shape, dimensions are analyzed to yield a huge amount of reduction in fuel consumption and increased performance. Owing to its simplicity of application and effectiveness we believe that it will enable us to consider its enhanced version for the grid effect of the staggered multiple winglets on the deflected mass flow of the wing system. The objective of the analysis were to compare the aerodynamic characteristics of two winglet configuration and to investigate the performance of two winglets shape simulated at selected cant angle of 0,45,60 degree.

Keywords: multiple winglets, induced drag, aerodynamics analysis, low speed aircrafts

Procedia PDF Downloads 477